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Found 3 papers, 1 papers with code
OU-CoViT: Copula-Enhanced Bi-Channel Multi-Task Vision Transformers with Dual Adaptation for OU-UWF Images
Furthermore, the novel architecture of OU-CoViT allows generalizability and extensions of our dual adaptation and Copula Loss to various ViT variants and large DL models on small medical datasets.
DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation
In this paper, we propose a novel Deformable U-Net (DeU-Net) to fully exploit spatio-temporal information from 3D cardiac MRI video, including a Temporal Deformable Aggregation Module (TDAM) and a Deformable Global Position Attention (DGPA) network.
Spatio-temporal deformable convolution for compressed video quality enhancement
Recent years have witnessed remarkable success of deep learning methods in quality enhancement for compressed video.
Ranked #3 on
Video Enhancement
on MFQE v2
